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@inproceedings{Strumbelj,
title = {A General Method for Visualizing and Explaining Black-box Regression Models},
author = {\v{S}trumbelj, Erik and Kononenko, Igor},
year = 2011,
booktitle = {Proceedings of the 10th International Conference on Adaptive and Natural Computing Algorithms - Volume Part II},
location = {Ljubljana, Slovenia},
publisher = {Springer-Verlag},
address = {Berlin, Heidelberg},
series = {Icannga'11},
pages = {21--30},
isbn = {978-3-642-20266-7},
url = {http://dl.acm.org/citation.cfm?id=1997005.1997009},
numpages = 10,
acmid = 1997009,
keywords = {SVM, neural networks, prediction, transparency}
}
@article{imeJLMR,
title = {An Efficient Explanation of Individual Classifications Using Game Theory},
author = {\v{S}trumbelj, Erik and Kononenko, Igor},
year = 2010,
month = mar,
journal = {Journal of Machine Learning Research},
publisher = {JMLR.org},
volume = 11,
pages = {1--18},
issn = {1532-4435},
url = {http://dl.acm.org/citation.cfm?id=1756006.1756007},
issue_date = {3/1/2010},
numpages = 18,
acmid = 1756007
}
@article{variableImportancePermutations,
author = {Aaron Fisher and Cynthia Rudin and Francesca Dominici},
title = {All models are Wrong, but many are Useful: Learning a variable's importance by studying an entire class of prediction models simultaneously},
journal = {Journal of Machine Learning Research},
year = {2019},
volume = {20},
number = {177},
pages = {1-81},
url = {http://jmlr.org/papers/v20/18-760.html}
}
@manual{R-factorMerger,
title = {factorMerger: The Merging Path Plot},
author = {Agnieszka Sitko and Aleksandra Grudziąż and Przemyslaw Biecek},
year = 2018,
url = {https://CRAN.R-project.org/package=factorMerger},
note = {R package version 0.3.6}
}
@manual{factorMerger,
title = {factorMerger: Hierarchical Algorithm for Post-Hoc Testing},
author = {Agnieszka Sitko and Przemyslaw Biecek},
year = 2017,
url = {https://github.com/MI2DataLab/factorMerger},
note = {R package version 0.3.4}
}
@manual{randomForestExplainer,
title = {randomForestExplainer: A set of tools to understand what is happening inside a Random Forest},
author = {Aleksandra Paluszynska and Przemyslaw Biecek},
year = 2017,
url = {https://github.com/MI2DataLab/randomForestExplainer},
note = {R package version 0.9}
}
@manual{R-randomForestExplainer,
title = {randomForestExplainer: Explaining and Visualizing Random Forests in Terms of Variable Importance},
author = {Aleksandra Paluszynska and Przemyslaw Biecek},
year = 2017,
url = {https://CRAN.R-project.org/package=randomForestExplainer},
note = {R package version 0.9}
}
@manual{R-ICEbox,
title = {ICEbox: Individual Conditional Expectation Plot Toolbox},
author = {Alex Goldstein and Adam Kapelner and Justin Bleich},
year = 2017,
url = {https://CRAN.R-project.org/package=ICEbox},
note = {R package version 1.1.2}
}
@article{ICEbox,
title = {Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation},
author = {Alex Goldstein and Adam Kapelner and Justin Bleich and Emil Pitkin},
year = 2015,
journal = {Journal of Computational and Graphical Statistics},
volume = 24,
number = 1,
pages = {44--65},
doi = {10.1080/10618600.2014.907095}
}
@inproceedings{LWRP,
title = {Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers},
author = {Alexander Binder and Gr{\'{e}}goire Montavon and Sebastian Bach and Klaus{-}Robert M{\"{u}}ller and Wojciech Samek},
year = "2016",
doi = "10.1007/978-3-319-44781-0_8",
isbn = "9783319447803",
volume = "9887 LNCS",
series = "Lecture Notes in Computer Science",
publisher = "Springer Verlag",
pages = "63--71",
booktitle = "Artificial Neural Networks and Machine Learning - 25th International Conference on Artificial Neural Networks, ICANN 2016, Proceedings",
note = "25th International Conference on Artificial Neural Networks and Machine Learning, ICANN 2016",
}
@manual{SAFE-arxiv,
title = {SAFE ML: Surrogate Assisted Feature Extraction for Model Learning},
author = {Alicja Gosiewska and Aleksandra Gacek and Piotr Lubon and Przemyslaw Biecek},
year = 2019,
url = {https://arxiv.org/abs/1902.11035}
}
@manual{iBreakDownRPackage,
title = {{iBreakDown: Uncertainty of Model Explanations for Non-additive Predictive Models}},
author = {Alicja Gosiewska and Przemyslaw Biecek},
year = 2019,
url = {https://arxiv.org/abs/1903.11420v1},
note = {R package version 1.3.3}
}
@manual{shapperPackage,
title = {{shapper: Wrapper of Python library shap}},
author = {Szymon Maksymiuk and Alicja Gosiewska and Przemyslaw Biecek},
year = 2019,
url = {https://github.com/ModelOriented/shapper},
note = {R package version 0.1.2}
}
@Manual{fastshapRpackage,
title = {{fastshap: Fast Approximate Shapley Values}},
author = {Brandon Greenwell},
year = {2020},
note = {R package version 0.0.5},
url = {https://CRAN.R-project.org/package=fastshap},
}
@manual{R-auditor,
title = {{auditor: Model Audit - Verification, Validation, and Error Analysis}},
author = {Alicja Gosiewska and Przemyslaw Biecek},
year = 2018,
url = {https://CRAN.R-project.org/package=auditor},
note = {R package version 0.2.1}
}
@article{auditorarxiv,
title = {{auditor}: an {R} Package for Model-Agnostic Visual Validation and Diagnostic},
author = {Alicja Gosiewska and Przemysław Biecek},
year = 2018,
journal = {ArXiv e-prints},
archiveprefix = {arXiv},
eprint = {1809.07763},
primaryclass = {stat.CO}
}
@article{randomForest,
title = {{Classification and regression by randomForest}},
author = {Andy Liaw and Matthew Wiener},
year = 2002,
journal = {R News},
volume = 2,
number = 3,
pages = {18--22},
url = {http://CRAN.R-project.org/doc/Rnews/}
}
@inproceedings{DeepLIFT,
author = {Shrikumar, Avanti and Greenside, Peyton and Kundaje, Anshul},
booktitle = {ICML},
editor = {Precup, Doina and Teh, Yee Whye},
ee = {http://proceedings.mlr.press/v70/shrikumar17a.html},
keywords = {dblp},
pages = {3145-3153},
publisher = {Proceedings of Machine Learning Research},
title = {Learning Important Features Through Propagating Activation Differences.},
url = {http://dblp.uni-trier.de/db/conf/icml/icml2017.html#ShrikumarGK17},
volume = 70,
year = 2017
}
@manual{MicrosofrCognitiveServices,
title = {{Microsoft Cognitive Services}},
author = {Azure},
year = 2019,
url = {https://azure.microsoft.com/en-en/services/cognitive-services/}
}
@article{BachLWRP,
title = {On {pixel}-{wise} {explanations} for {non}-{linear} {classifier} {decisions} by {layer}-{Wise} {relevance} {propagation}},
author = {Bach, Sebastian and Binder, Alexander and Montavon, Grégoire and Klauschen, Frederick and Müller, Klaus-Robert and Samek, Wojciech},
year = 2015,
month = jul,
journal = {Plos One},
volume = 10,
number = 7,
pages = {e0130140},
doi = {10.1371/journal.pone.0130140},
issn = {1932-6203},
url = {http://dx.plos.org/10.1371/journal.pone.0130140},
urldate = {2018-09-24},
language = {en},
editor = {Suarez, Oscar Deniz}
}
@article{spiral1988,
title = {A Spiral Model of Software Development and Enhancement},
author = {Barry Boehm},
year = 1988,
pages = {61--72},
volume = {21(5)},
journal = {{ IEEE Computer, IEEE}}
}
@manual{DARPA,
title = {Inside DARPA’s effort to create explainable artificial intelligence},
author = {Ben Dickson},
year = 2019,
url = {https://bdtechtalks.com/2019/01/10/darpa-xai-explainable-artificial-intelligence/}
}
@inproceedings{hoover2019exbert,
title = "ex{BERT}: A Visual Analysis Tool to Explore Learned Representations in {T}ransformer Models",
author = "Hoover, Benjamin and
Strobelt, Hendrik and
Gehrmann, Sebastian",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2020.acl-demos.22",
pages = "187--196"
}
@article{mlr,
title = {{mlr: Machine Learning in R}},
author = {Bernd Bischl and Michel Lang and Lars Kotthoff and Julia Schiffner and Jakob Richter and Erich Studerus and Giuseppe Casalicchio and Zachary M. Jones},
year = 2016,
journal = {Journal of Machine Learning Research},
volume = 17,
number = 170,
pages = {1--5},
url = {http://jmlr.org/papers/v17/15-066.html}
}
@article{pdpRPackage,
title = {pdp: An {R} package for constructing partial dependence plots},
author = {Brandon M. Greenwell},
year = 2017,
journal = {{The R Journal}},
volume = 9,
number = 1,
pages = {421--436},
url = {https://journal.r-project.org/archive/2017/RJ-2017-016/index.html}
}
@book{CARTtree,
title = {Classification and Regression Trees},
author = {Breiman, L. and Friedman, J. H. and Olshen, R. A. and Stone, C. J.},
year = 1984,
publisher = {Wadsworth and Brooks},
address = {Monterey, CA}
}
@manual{R-nnet,
title = {nnet: Feed-Forward Neural Networks and Multinomial Log-Linear Models},
author = {Brian Ripley},
year = 2016,
url = {https://CRAN.R-project.org/package=nnet},
note = {R package version 7.3-12}
}
@article{RightToExpl,
title={{European Union} regulations on algorithmic decision-making and a “Right to explanation”},
volume={38}, url={https://www.aaai.org/ojs/index.php/aimagazine/article/view/2741},
DOI={10.1609/aimag.v38i3.2741},
number={3},
journal={AI Magazine},
author={Goodman, Bryce and Flaxman, Seth},
year={2017},
pages={50-57}
}
@article{IBMWatson,
title = {{IBM’s Watson supercomputer recommended ‘unsafe and incorrect’ cancer treatments, internal documents show}},
author = {Casey Ross and Ike Swetliz},
year = 2018,
journal = {Statnews},
url = {https://www.statnews.com/2018/07/25/ibm-watson-recommended-unsafe-incorrect-treatments/},
note = {https://bit.ly/38mVxSW}
}
@article{RightToExpl2,
title = {{Rethinking explainable machines: The GDPR's Right to Explanation debate and the rise of algorithmic audits in enterprise}},
author = {Casey, Bryan and Farhangi, Ashkon and Vogl, Roland},
year = 2019,
journal = {Berkeley Technology Law Journal},
volume = 34,
pages = {143--188}
}
@book{molnar2019,
title = {{Interpretable Machine Learning}},
author = {Christoph Molnar},
year = 2019,
note = {\url{https://christophm.github.io/interpretable-ml-book/}},
subtitle = {A Guide for Making Black Box Models Explainable}
}
@book{molnar,
title = {Interpretable Machine Learning},
author = {Christoph Molnar},
year = 2018,
publisher = {https://christophm.github.io/interpretable-ml-book/},
note = {\url{https://christophm.github.io/interpretable-ml-book/}}
}
@manual{R-iml,
title = {iml: Interpretable Machine Learning},
author = {Christoph Molnar},
year = 2018,
url = {https://CRAN.R-project.org/package=iml},
note = {R package version 0.7.0}
}
@article{imlRPackage,
title = {{iml: An R package for Interpretable Machine Learning}},
author = {Christoph Molnar and Bernd Bischl and Giuseppe Casalicchio},
year = 2018,
journal = {Journal of Open Source Software},
volume = 3,
number = 26,
pages = 786,
doi = {10.21105/joss.00786},
url = {http://joss.theoj.org/papers/10.21105/joss.00786}
}
@article{AppleCreditCard,
title = {{Apple co-founder Steve Wozniak says Apple Card discriminated against his wife}},
author = {Clare Duffy},
year = 2019,
journal = {CNN Business},
url = {https://edition.cnn.com/2019/11/10/business/goldman-sachs-apple-card-discrimination/index.html},
note = {https://cnn.it/36i6kLq}
}
@article{wine2009,
title = {Modeling wine preferences by data mining from physicochemical properties},
author = {Cortez, Paulo and Cerdeira, António and Almeida, Fernando and Matos, Telmo and Reis, José},
year = 2009,
month = nov,
journal = {Decision Support Systems},
volume = 47,
number = 4,
pages = {547--553},
doi = {10.1016/j.dss.2009.05.016},
issn = 1679236,
url = {http://linkinghub.elsevier.com/retrieve/pii/S0167923609001377},
urldate = {2017-10-24},
language = {en}
}
@manual{ALEPlot,
title = {ALEPlot: Accumulated Local Effects (ALE) Plots and Partial Dependence (PD) Plots},
author = {Dan Apley},
year = 2017,
url = {https://CRAN.R-project.org/package=ALEPlot},
note = {R package version 1.0}
}
@manual{ALEPlotRPackage,
title = {ALEPlot: Accumulated Local Effects (ALE) Plots and Partial Dependence (PD) Plots},
author = {Dan Apley},
year = 2018,
url = {https://CRAN.R-project.org/package=ALEPlot},
note = {R package version 1.1}
}
@manual{R-ALEPlot,
title = {ALEPlot: Accumulated Local Effects (ALE) Plots and Partial Dependence (PD) Plots},
author = {Dan Apley},
year = 2018,
url = {https://CRAN.R-project.org/package=ALEPlot},
note = {R package version 1.1}
}
@manual{sjPlot,
title = {sjPlot: Data Visualization for Statistics in Social Science},
author = {Daniel Lüdecke},
year = 2017,
url = {https://CRAN.R-project.org/package=sjPlot},
note = {R package version 2.4.0}
}
@article{ALEPlot2,
title = {Visualizing the Effects of Predictor Variables in Black Box Supervised Learning Models},
author = {Daniel W. Apley and Jingyu Zhu},
year = 2019,
journal = {CoRR},
volume = {abs/1612.08468},
url = {http://arxiv.org/abs/1612.08468},
archiveprefix = {arXiv},
eprint = {1612.08468}
}
@manual{xgboostExplainer,
title = {xgboostExplainer: An R package that makes xgboost models fully interpretable},
author = {David Foster},
year = 2017,
url = {https://github.com/AppliedDataSciencePartners/xgboostExplainer/},
note = {R package version 0.1}
}
@manual{R-xgboostExplainer,
title = {xgboostExplainer: XGBoost Model Explainer},
author = {David Foster},
year = 2018,
note = {R package version 0.1}
}
@manual{DARPA2,
title = {Explainable Artificial Intelligence (XAI)},
author = {David Gunning},
year = 2017,
url = {https://www.darpa.mil/attachments/XAIProgramUpdate.pdf}
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